scholarly journals Improved Deep Belief Networks (IDBN) Dynamic Model-Based Detection and Mitigation for Targeted Attacks on Heavy-Duty Robots

2018 ◽  
Vol 8 (5) ◽  
pp. 676 ◽  
Author(s):  
Lianpeng Li ◽  
Lun Xie ◽  
Weize Li ◽  
Zhenzong Liu ◽  
Zhiliang Wang
2016 ◽  
Vol 8 (3/4) ◽  
pp. 237 ◽  
Author(s):  
Mohamed Benouis ◽  
Mohamed Senouci ◽  
Redouane Tlemsani ◽  
Lotfi Mostefai

2016 ◽  
Vol 8 (3/4) ◽  
pp. 237
Author(s):  
Mohamed Benouis ◽  
Mohamed Senouci ◽  
Redouane Tlemsani ◽  
Lotfi Mostefai

Author(s):  
Vidhusha Srinivasan ◽  
N. Udayakumar ◽  
Kavitha Anandan

Background: The spectrum of autism encompasses High Functioning Autism (HFA) and Low Functioning Autism (LFA). Brain mapping studies have revealed that autism individuals have overlaps in brain behavioural characteristics. Generally, high functioning individuals are known to exhibit higher intelligence and better language processing abilities. However, specific mechanisms associated with their functional capabilities are still under research. Objective: This work addresses the overlapping phenomenon present in autism spectrum through functional connectivity patterns along with brain connectivity parameters and distinguishes the classes using deep belief networks. Methods: The task-based functional Magnetic Resonance Images (fMRI) of both high and low functioning autistic groups were acquired from ABIDE database, for 58 low functioning against 43 high functioning individuals while they were involved in a defined language processing task. The language processing regions of the brain, along with Default Mode Network (DMN) have been considered for the analysis. The functional connectivity maps have been plotted through graph theory procedures. Brain connectivity parameters such as Granger Causality (GC) and Phase Slope Index (PSI) have been calculated for the individual groups. These parameters have been fed to Deep Belief Networks (DBN) to classify the subjects under consideration as either LFA or HFA. Results: Results showed increased functional connectivity in high functioning subjects. It was found that the additional interaction of the Primary Auditory Cortex lying in the temporal lobe, with other regions of interest complimented their enhanced connectivity. Results were validated using DBN measuring the classification accuracy of 85.85% for high functioning and 81.71% for the low functioning group. Conclusion: Since it is known that autism involves enhanced, but imbalanced components of intelligence, the reason behind the supremacy of high functioning group in language processing and region responsible for enhanced connectivity has been recognized. Therefore, this work that suggests the effect of Primary Auditory Cortex in characterizing the dominance of language processing in high functioning young adults seems to be highly significant in discriminating different groups in autism spectrum.


2017 ◽  
Vol 16 (2) ◽  
pp. 129-136 ◽  
Author(s):  
Tianming Zhan ◽  
Yi Chen ◽  
Xunning Hong ◽  
Zhenyu Lu ◽  
Yunjie Chen

Processes ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 1036
Author(s):  
Yunxia Li ◽  
Lei Li

A countershaft brake is used as a transmission brake (TB) to realize synchronous shifting by reducing the automated mechanical transmission (AMT) input shaft’s speed rapidly. This process is performed to reduce shifting time and improve shifting quality for heavy-duty vehicles equipped with AMT without synchronizer. To improve controlled synchronous shifting, the AMT input shaft’s equivalent resistance torque and the TB’s characteristic parameters are studied. An AMT dynamic model under neutral gear position is analyzed during the synchronous control interval. A dynamic model of the countershaft brake is discussed, and its control flow is given. The parameter identification method of the AMT input shaft’s equivalent resistance torque is given on the basis of the least squares algorithm. The parameter identification of the TB’s characteristic parameters is proposed on the basis of the recursive least squares method (RLSM). Experimental results show that the recursive estimations of the TB’s characteristic parameters under different duty cycles of the TB solenoid valve, including brake torque estimation, estimation accuracy, and braking intensity estimation, can be effectively estimated. The research provides some reliable evidence to further study the synchronous shifting control schedule for heavy-duty vehicles with AMT.


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